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One might ask why we would ever want to create robots that can do human work when we have so many people who need jobs. The goal of robotics should not be to replace humans with robots, but rather to improve productivity and safety, removing humans from harm’s way and enabling them to focus on things that humans should be doing.

We can agree that humans shouldn’t be carrying heavy loads, exposing themselves to radiation or finding land mines. What is less clear is the gray area, where the line that divides human and robot competency is becoming blurred. People wonder whether robots will displace their jobs. It’s an important question, especially because it’s already obvious that robotics has impacted the workforce.

Which industries will see the greatest integration of robotics, and which ones are likely not to be impacted? There are a number of misconceptions, and even fears, about the assimilation of robots in the workplace. Overcoming these involves a greater understanding of the value of humans versus robots and the current technological limitations to robots. Including robots in the workplace is not an “all or nothing” scenario. The most important question is how humans and robots should work together to improve quality and safety rather than how robots can replace humans.

Robots and the workforce

What people rarely understand is that robotics doesn’t necessarily produce a net loss in human jobs. One of my colleagues helped develop the Kiva robots, which eventually became the basis of Amazon’s logistic centers. He explained that the original appeal of robots was that they would reduce the human labor workforce. That never happened. What did happen was that the robots massively improved the productivity of each human, allowing Amazon to scale operations. No human was ever fired — in fact, more humans were hired.

The same thing was true for my work with military robots. The original premise signed into law by Congress was that half of our armed forces would become unmanned. The original aim was to cut labor costs, but, as with Amazon, the labor savings never came. What did happen is that robots saved lives and improved the safety and productivity of each soldier by conducting tasks like landmine detection and mapping out radiation and chemical spills. It also created a lot of jobs associated with building, maintaining and using robots.

It is entirely possible that we are becoming robot-like faster than robots are becoming like humans.

A Pew Research Center study indicated that although technology is often sold as a means to reduce labor, it may actually create more high-paying jobs than the low-paying jobs it eliminates. However, the study also indicated a broad concern regarding how the use of robots will play out. When asked how robotics and self-driving cars would impact the workforce, 48 percent of experts surveyed believed that robots would directly displace human workers for both blue-collar and white-collar jobs. On the other hand, 52 percent believed that robotics will create more jobs than it displaces.

Gartner estimates there are 6.4 billion “connected things” in the world around us. The volume of sensor data coming from these connected entities is expected to increase dramatically, accounting for more and more of the total data in our world. Robots are poised to be crucial arbiters of the new, machine-intensive ecosystem of sensors, interfaces and actuators that we are building up all around us at home and in the workplace. Robots can handle the complexity of this increasingly intricate world, allowing our attention to focus on the humans around us rather than on screens, buttons and keys.

Defining roles: robots versus humans

The more time we spend training ourselves to surf the net and text, the less our lives resemble human lives of the last century. Today it is entirely possible that we are becoming robot-like faster than robots are becoming like humans. This is not an inevitable course, but rather something we are consciously deciding to do. We need to carefully consider how much we value direct human interaction.

Part of this is preference, but profit and performance considerations may override our preferences. From a performance perspective, humans and robots are not necessarily good at the same things; we need to both comprehend and plan for the differences between humans and robots. In biology, co-evolutionary development occurs when two species evolve in relation to each other. In an ideal future, robotics applications will allow us to embrace the unique, vital essence of what it means to be human — creativity, imagination, love — and prevent the need for us to become more like machines.

We need to objectively differentiate ourselves and our skills from what robots can do. The general wisdom, based on understanding of robots from the past decade, is that humans are good at high-level decision making and understanding the purpose and context for a task. Robots are generally good at repetitive physical labor and reactive, high-precision tasks that require careful attention to detail. With a new generation of robots on the way, this understanding may need to change.

Job limitations and robotics

I seem to have very interesting discussions whenever I get a haircut. One day I was explaining to my hairdresser that I work with robots and she stopped cutting, visibly upset and remarked that she would probably be out of a job before too long because of the development of robotic intelligence. I thought about it, and realized that robots would most likely replace my job before they replaced hers.

Her job was really, really hard. She had to take hopelessly vague tasking like: “Give me a George Clooney haircut but kind of a bit more fun and crazy.” What does that mean? I can pretty well guarantee that a robot won’t ever know what that means. Regardless of trying to understand the semantics, a much harder task is figuring out how many small scissor cuts will result in an emerging look. Cutting hair is not an easy job; I know I could never do it. I believe it would scare any robot as well.

We need to ensure a framework where human input and robot input can be properly interwoven.

I told my hairdresser she had nothing to worry about, but she still looked at me skeptically. What she didn’t realize is that even if robots could cut hair effectively, she still had a major advantage. She had softly massaged my head and neck before she started cutting and she breezily discussed just about any topic while making her customer feel at ease.

Machines will impact the jobs of surgeons and professors long before they impact her job. We already have robots that perform surgical tasks more precisely and reliably than human hands. Likewise, distance education and automated testing are already changing the landscape for education. Hair cutting remains a domain where human artisans reign supreme.

Humans excel when resourcefulness and contextual understanding are important. It is difficult to imagine a robot with the broad range of problem solving, general purpose knowledge and dexterity necessary to be a facility superintendent: fixing broken garbage disposals and broken toilets, maintaining the boiler, replacing a leaky pipe, etc. Robots struggle in these unstructured environments where MacGyver-like problem solving is necessary. Like the hairdresser, apartment superintendents have little to fear from robots any time soon. As we consider the complexity of various human jobs, we must rethink not only what we value in general, but how we pay people in particular. Maybe we’ll end up paying hairdressers and building superintendents more than surgeons and professors?

It’s not an “either-or” decision

Robots will change the contours of our workforce, but hopefully for the better. Even the professor and surgeon, who can already see impact from various forms of robotics and AI, need not feel that technology is replacing them. The advent of the calculator did not steal something vital from mathematicians. It did change what we value from them. Few of us feel enmity with calculators because we’re generally happy to let calculators outperform us in that arena. Robots will be much more than calculators, but still the key will be to ensure that we value the right things.

We need to ensure a framework where human input and robot input can be properly interwoven. All too often, we focus on either full human control or full autonomy, and neither of these is likely to be optimal.

While working with the Department of Energy we found that operators who had spent many years honing their ability to drive robots with joysticks were quite resistant to the notion that the robots could do the driving for them. In one experiment, operators drove the course twice, once in a mode where the robot took no initiative and once in a shared control mode where the human felt like they were in control but the robot wove its way through hallways and openings.

As expected, performance was significantly better in the mode where the robot helped with the driving. Less expected were the operators’ responses when asked about their “feeling of control.” They actually reported feeling more in control while using the mode where the robot did most of the driving. They took the credit for the good driving when really it was robot initiative that made them successful.

Humans often don’t know what they’re good at, but the introduction of a well-structured human-robot interaction approach can help us maintain high-level control while taking away the low-level details.

If we can get the task allocation right, the humans of the future won’t be fighting with robots to shovel dirt, find landmines or drive mining equipment. Rather, humans will be caring for people and having interesting conversations about how to make the world a better place. They should be doing whatever they love and spending time with whomever they love — which will hopefully not be a robot.

Despite persistent fears regarding robot overlords, we will be as free as we choose to make ourselves. We can do this not by fighting with robots but by fighting fiercely to maintain our distinctness and our essential nature.

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OverviewBased in San Francisco, Kiva is an international non-profit organization that enables families to make small loans to entrepreneurs in developing countries. It has crowdfunded over 705 million U.S. dollars in microloans to over one million entrepreneurs in 86 countries. Founded in 2005, Kiva covers its costs primarily through optional donations as well as through support from grants and sponsors.